Triple
T38188799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Manchester |
E1005393
|
entity |
| Predicate | hasTertiaryMode |
P198278
|
FINISHED |
| Object | air |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: air | Statement: [London–Manchester, hasTertiaryMode, air]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTertiaryMode Context triple: [London–Manchester, hasTertiaryMode, air]
-
A.
hasTertiaryComponent
Indicates that an entity includes or is associated with a third-level (tertiary) component within a hierarchical structure or system.
-
B.
hasPrimaryModeSupported
Indicates that an entity supports a particular mode as its main or default mode of operation.
-
C.
hasNumberOfMainModes
Indicates the relationship that specifies how many primary or main modes (e.g., ways of operation or types) are associated with a given entity.
-
D.
hasModeSystem
Indicates that one entity operates under, or is associated with, a particular mode defined or managed by another system.
-
E.
hasModeCategory
Indicates that something is associated with or classified under a particular mode category (e.g., type or manner of operation or behavior).
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76dbc22c481908139b694ffde7a0c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fed6da0390819096b88ef4714b144e |
completed | May 9, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69fed53517d081909966f31707625f1a |
completed | May 9, 2026, 6:33 a.m. |
| PDg | Predicate description generation | batch_69fed6d90f2081909cd21e5e973a6b89 |
completed | May 9, 2026, 6:40 a.m. |
Created at: May 3, 2026, 4:29 p.m.